Yehong Li
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Yehong Li has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Henry Du
Stevens Institute of Technology
2 shared publications - Silvana Andreescu
Clarkson University
2 shared publications - Tianhang Huo
Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, USA
2 shared publications - Yu-Ping Huang
Department of Physics, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ 07030, USA
2 shared publications - Santosh Kumar
Stevens Institute of Technology
1 shared publication
Latest Publications
- Open Access
Quantitative Analysis of Perfluorooctanoic Acid and Perfluorooctane Sulfonate Mixtures Using 3D Surface-Enhanced Raman Spectroscopy with Single-Photon Detection
Per- and polyfluoroalkyl substances (PFASs) are persistent environmental contaminants that commonly occur as mixtures, yet their weak Raman scattering and overlapping vibrational features make direct optical quantification challenging. Here, we develop a plasmonic nanosensing platform that integrates three-dimensional Ag nanoparticle surface-enhanced Raman spectroscopy (SERS) substrates with single-photon Raman readout for quantitative analysis of binary perfluorooctanoic acid (PFOA)/perfluorooctane sulfonate (PFOS) mixtures. The multilayer silver nanoparticle (AgNP) architecture provides dense electromagnetic hot spots to amplify weak PFAS signatures, while photon-counting detection improves the measurement of low-intensity Raman features. Mixed spectra obtained from a 4 × 4 concentration matrix spanning to M exhibited substantial peak overlap, band broadening, and concentration-dependent spectral contour changes, highlighting the limitations of single-band calibration. Full-spectrum multivariate regression was therefore used to extract composition-dependent information from the coupled SERS response. Under nested cross-validation with replicates grouped by mixture composition, both partial least squares regression and linear support vector regression captured the main concentration-dependent spectral variation, achieving values of approximately 0.81–0.87 across the two analytes and identifying experimental concentration levels within one adjacent level after nearest-level assignment. These results demonstrate that coupling engineered plasmonic AgNP substrates with single-photon Raman detection enables mixture-resolved PFAS quantification from weak and overlapping SERS signatures, providing a nanomaterial-enabled framework for environmental molecular sensing.Open AccessQuantitative Analysis of Perfluorooctanoic Acid and Perfluorooctane Sulfonate Mixtures Using 3D Surface-Enhanced Raman Spectroscopy with Single-Photon Detection
Per- and polyfluoroalkyl substances (PFASs) are persistent environmental contaminants that commonly occur as mixtures, yet their weak Raman scattering and overlapping vibrational features make direct optical quantification challenging. Here, we develop a plasmonic nanosensing platform that integrates three-dimensional Ag nanoparticle surface-enhanced Raman spectroscopy (SERS) substrates with single-photon Raman readout for quantitative analysis of binary perfluorooctanoic acid (PFOA)/perfluorooctane sulfonate (PFOS) mixtures. The multilayer silver nanoparticle (AgNP) architecture provides dense electromagnetic hot spots to amplify weak PFAS signatures, while photon-counting detection improves the measurement of low-intensity Raman features. Mixed spectra obtained from a 4 × 4 concentration matrix spanning to M exhibited substantial peak overlap, band broadening, and concentration-dependent spectral contour changes, highlighting the limitations of single-band calibration. Full-spectrum multivariate regression was therefore used to extract composition-dependent information from the coupled SERS response. Under nested cross-validation with replicates grouped by mixture composition, both partial least squares regression and linear support vector regression captured the main concentration-dependent spectral variation, achieving values of approximately 0.81–0.87 across the two analytes and identifying experimental concentration levels within one adjacent level after nearest-level assignment. These results demonstrate that coupling engineered plasmonic AgNP substrates with single-photon Raman detection enables mixture-resolved PFAS quantification from weak and overlapping SERS signatures, providing a nanomaterial-enabled framework for environmental molecular sensing. - Open Access
- 6 May 2025
- Published by Springer Nature in Research Square
Quantitative Measurements of PFAS at Femtomole Concentrations via Integrated SERS and Single Photon Detection Methods
Per- and polyfluoroalkyl substances (PFAS) pose significant environmental and health concerns, necessitating their efficient and accurate identification to facilitate their eventual mitigation from the environment. Surface-enhanced Raman spectroscopy (SERS) enables highly sensitive and precise molecular identification, but trace-level detection of chemicals and fluorescence interference remain significant challenges. Here, we present a uniform 3D AgNP@Si substrate for SERS, leveraging photon counting to achieve susceptible and low-fluorescence detection. This approach enables the detection of PFAS, including perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), at concentrations as low as 10− 15 M, with Rhodamine 6G (R6G) used as a model analyte. Additionally, the quantitative analysis demonstrated a strong logarithmic relationship between Raman intensity and analyte concentration, with high correlation coefficients (R2 = 0.98 for R6G and 0.97 for PFOA and PFOS). This pioneering approach offers a promising alternative to current analytical techniques for monitoring PFAS and other contaminants in the environment.
- 6 May 2025
- Published by Springer Nature in Research Square
Open AccessQuantitative Measurements of PFAS at Femtomole Concentrations via Integrated SERS and Single Photon Detection Methods
Per- and polyfluoroalkyl substances (PFAS) pose significant environmental and health concerns, necessitating their efficient and accurate identification to facilitate their eventual mitigation from the environment. Surface-enhanced Raman spectroscopy (SERS) enables highly sensitive and precise molecular identification, but trace-level detection of chemicals and fluorescence interference remain significant challenges. Here, we present a uniform 3D AgNP@Si substrate for SERS, leveraging photon counting to achieve susceptible and low-fluorescence detection. This approach enables the detection of PFAS, including perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), at concentrations as low as 10− 15 M, with Rhodamine 6G (R6G) used as a model analyte. Additionally, the quantitative analysis demonstrated a strong logarithmic relationship between Raman intensity and analyte concentration, with high correlation coefficients (R2 = 0.98 for R6G and 0.97 for PFOA and PFOS). This pioneering approach offers a promising alternative to current analytical techniques for monitoring PFAS and other contaminants in the environment.